Fairness in machine learning: A survey

Cited by (646)

Items 101–200 of 646

1. Consumer-side fairness in recommender systems: a systematic survey of methods and evaluation
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2. EHR-based prediction modelling meets multimodal deep learning: A systematic review of structured and textual data fusion methods
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3. A survey on group fairness in federated learning: challenges, taxonomy of solutions and directions for future research
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4. TARA: Training and Representation Alteration for AI Fairness and Domain Generalization
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5. Fairness-aware practices from developers’ perspective: A survey
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6. Machine learning in biological research: key algorithms, applications, and future directions
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7. Enforcing Group Fairness in Algorithmic Decision Making: Utility Maximization Under Sufficiency
   Joachim Baumann, Anikó Hannák, Christoph Heitz · 2022 · ACM Conference on Fairness, Accountability, and Transparency (FAccT)
8. Debiaser for Multiple Variables to enhance fairness in classification tasks
   Giordano d’Aloisio, Andrea D’Angelo, Antinisca Di Marco, Giovanni Stilo · 2022 · Information Processing & Management
9. Ethical Quantum Computing: A Roadmap
   Elija Perrier · 2021 · arXiv (Cornell University)
10. High-risk artificial intelligence
    Sunyaev, Ali, Benlian, Alexander, Pfeiffer, Jella, Jussupow, Ekaterina, Thiebes, Scott, Maedche, Alexander, Gawlitza, Joshua · 2025 · Business & Information Systems Engineering
11. Development and validation of predictive models for COVID-19 outcomes in a safety-net hospital population
    Boran Hao, Yang Hu, Shahabeddin Sotudian, Zahra Zad, William G. Adams, Sabrina A. Assoumou, Heather Hsu, Rebecca Grochow Mishuris, Ioannis Ch. Paschalidis · 2022 · Journal of the American Medical Informatics Association
12. Identifying the limitations associated with machine learning techniques in performing accounting tasks
    Liezl Smith, Christiaan Lamprecht · 2024 · Journal of financial reporting & accounting
13. Travel Demand Forecasting: A Fair AI Approach
    Xiaojian Zhang, Qian Ke, Xilei Zhao · 2024 · IEEE Transactions on Intelligent Transportation Systems
14. A Comparison of Bias Mitigation Techniques for Educational Classification Tasks Using Supervised Machine Learning
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15. Improving medical machine learning models with generative balancing for equity and excellence
    Brandon Theodorou, Benjamin P. Danek, Venkat Tummala, S. D. Madhu Kumar, Bradley Malin, Jimeng Sun · 2025 · npj Digital Medicine
16. Achieving Long-Term Fairness in Sequential Decision Making
    Yaowei Hu, Lu Zhang · 2022 · Proceedings of the AAAI Conference on Artificial Intelligence
17. Editorial: Big data and machine learning in sociology
    Heinz Leitgöb, Dimitri Prandner, Tobias Wolbring · 2023 · Frontiers in Sociology
18. Fairness Evaluation with Item Response Theory
    Ziqi Xu, Sevvandi Kandanaarachchi, Cheng Soon Ong, Eirini Ntoutsi · 2025 · International World Wide Web Conference (WWW)
19. A Systematic Literature Review on Equity and Technology in HCI and Fairness: Navigating the Complexities and Nuances of Equity Research
    Seyun Kim, Yuanchen Bai, Haiyi Zhu, Motahhare Eslami · 2025 · Proceedings of the ACM on Human-Computer Interaction
20. Toward fair medical advice: Addressing and mitigating bias in large language model-based healthcare applications
    Haohui Lu, Ye Lin, Zhidong Li, Man Lung Yiu, Yu Gao, Shahadat Uddin · 2025 · Artificial Intelligence in Medicine
21. Quantum Fair Machine Learning
    Elija Perrier · 2021 · Proceedings of the AAAI/ACM Conference on AI Ethics and Society
22. A Personalized Framework for Consumer and Producer Group Fairness Optimization in Recommender Systems
    Hossein A. Rahmani, Mohammadmehdi Naghiaei, Yashar Deldjoo · 2024 · ACM Transactions on Recommender Systems
23. Comprehensive Validation on Reweighting Samples for Bias Mitigation via AIF360
    Christina Hastings Blow, Lijun Qian, Camille A. Gibson, Pamela Obiomon, Xishuang Dong · 2024 · Applied Sciences
24. A novel approach for assessing fairness in deployed machine learning algorithms
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25. FairXAI - A Taxonomy and Framework for Fairness and Explainability Synergy in Machine Learning
    Resmi Ramachandranpillai, Ricardo A. Baeza-Yates, Fredrik Heintz · 2025 · IEEE Transactions on Neural Networks and Learning Systems
26. Adaptive Sampling for Minimax Fair Classification
    Shubhanshu Shekhar, Fields, Greg, Mohammad Ghavamzadeh, Tara Javidi · 2021 · arXiv (Cornell University)
27. Bias in Federated Learning: A Comprehensive Survey
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28. A Multi-Objective Framework for Balancing Fairness and Accuracy in Debiasing Machine Learning Models
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29. SFFL: Self-aware fairness federated learning framework for heterogeneous data distributions
    Jiale Zhang, Ye Li, Di Wu, Yanchao Zhao, Palaiahnakote Shivakumara · 2025 · Expert Systems with Applications
30. Bias and Fairness in Computer Vision Applications of the Criminal Justice System
    Sophie Noiret, Jennifer Lumetzberger, Martin Kampel · 2021 · IEEE Symposium Series on Computational Intelligence (SSCI)
31. Unfair! Perceptions of Fairness in Human-Robot Teams
    Mai Lee Chang, J. Gregory Trafton, J. Malcolm McCurry, Andrea L. Thomaz · 2021 · IEEE RO-MAN
32. MultiFair: Model Fairness With Multiple Sensitive Attributes
    Huan Tian, Bo Liu, Tianqing Zhu, Wanlei Zhou, Philip S. Yu · 2024 · IEEE Transactions on Neural Networks and Learning Systems
33. On Explaining Unfairness: An Overview
    Christos Fragkathoulas, Vasiliki Papanikou, Danae Pla Karidi, Evaggelia Pitoura · 2024 · IEEE International Conference on Data Engineering Workshops (ICDEW)
34. Model-Agnostic Causal Embedding Learning for Counterfactually Group-Fair Recommendation
    Xiao Zhang, Teng Shi, Jun Xu, Zhenhua Dong, Ji-Rong Wen · 2024 · IEEE Transactions on Knowledge and Data Engineering
35. Explainable Machine Learning and Graph Neural Network Approaches for Predicting Employee Attrition
    Christopher Makanga, Dennis Mukwaba, Clare Linda Agaba, Sudi Murindanyi, Tibakanya Joseph, Nakayiza Hellen, Ggaliwango Marvin · 2024 · International Conference on Contemporary Computing
36. An Empirical Comparison of Bias Reduction Methods on Real-World Problems in High-Stakes Policy Settings
    Hemank Lamba, Kit T. Rodolfa, Rayid Ghani · 2021 · ACM SIGKDD Explorations Newsletter
37. Fairness and Discrimination in Information Access Systems
    Michael D. Ekstrand, Anubrata Das, Robin Burke, Fernando Díaz · 2021 · arXiv (Cornell University)
38. Dbias: Detecting biases and ensuring Fairness in news articles
    Shaina Raza, Deepak John Reji, Chen Ding · 2022 · Research Square
39. Fair Machine Learning in Healthcare: A Survey
    Feng, Qizhang, Du, Mengnan, Zou, Na, Hu, Xia · 2025 · IEEE Transactions on Artificial Intelligence
40. Unveiling Accuracy-Fairness Trade-Offs
    Raymond A. Opoku, Bo Pei, Wanli Xing · 2025 · Journal of Learning Analytics
41. Performance, Fairness, and Explainability in AI-Based Credit Scoring: A Systematic Literature Review
    Rashed A. Bahlool, Nabil Hewahi, Wael Mohamed Elmedany · 2026 · Journal of risk and financial management
42. Fair classification via domain adaptation: A dual adversarial learning approach
    Yueqing Liang, Canyu Chen, Tian Tian, Kai Shu · 2023 · Frontiers in Big Data
43. FRAMM: Fair ranking with missing modalities for clinical trial site selection
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44. On prediction-modelers and decision-makers: why fairness requires more than a fair prediction model
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45. Properties of Fairness Measures in the Context of Varying Class Imbalance and Protected Group Ratios
    Dariusz Brzeziński, Julia Stachowiak, Jerzy Stefanowski, Izabela Szczęch, Robert Susmaga, Sofya Aksenyuk, Uladzimir Ivashka, Oleksandr Yasinskyi · 2024 · ACM Transactions on Knowledge Discovery from Data
46. Algorithmic Subjectivities
    Eric P. S. Baumer, Alex S. Taylor, Jed R. Brubaker, Micki McGee · 2024 · ACM Transactions on Computer-Human Interaction
47. Strategies to improve fairness in artificial intelligence:A systematic literature review
    António Trigo, Nubia Stein, Fernando Paulo Belfo · 2024 · Education for Information
48. An Interactive Approach to Bias Mitigation in Machine Learning
    Wang, Hao, Mukhopadhyay, Snehasis, Xiao, Yunyu, Fang, Shiaofen · 2021 · 2021 IEEE 20th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)
49. Application of fairness to healthcare, organizational justice, and finance: A survey
    Pardis Birzhandi, Yoon-Sik Cho · 2022 · Expert Systems with Applications
50. A fairness-focused approach to recidivism prediction: implications for accuracy, trust, and equity
    Michael Mayowa Farayola, Irina Tal, Takfarinas Saber, Regina Connolly, Malika Bendechache · 2025 · AI & Society
51. Reducing Bias in Sentiment Analysis Models Through Causal Mediation Analysis and Targeted Counterfactual Training
    Yifei Da, Matías Nicolás Bossa, Abel Díaz Berenguer, Hichem Sahli B · 2024 · IEEE Access
52. Ethical considerations in AI-based user profiling for knowledge management: A critical review
    Daniel Kogi Njiru, David Muchangi Mugo, Faith Mueni Musyoka · 2025 · Telematics and Informatics Reports
53. Federated Learning for All: A Reinforcement Learning-Based Approach for Ensuring Fairness in Client Selection
    Saeedeh Ghazi, Saeed Farzi, Amirhossein Nikoofard · 2025 · IEEE Access
54. What Is Fair? Defining Fairness in Machine Learning for Health
    Jianhui Gao, Benson Chou, Zachary Ryan McCaw, Hilary Thurston, Paul Varghese, Chuan Hong, Jessica L. Gronsbell · 2025 · Statistics in Medicine
55. Exploiting Fairness to Enhance Sensitive Attributes Reconstruction
    Julien Ferry, Ulrich Aïvodji, Sébastien Gambs, Marie‐José Huguet, Mohamed Siala · 2023 · IEEE Conference on Secure and Trustworthy Machine Learning (SaTML)
56. Group Fairness in Prediction-Based Decision Making: From Moral Assessment to Implementation
    Joachim Baumann, Christoph Heitz · 2022 · IEEE Swiss Conference on Data Science (SDS)
57. Fair Graph Auto-Encoder for Unbiased Graph Representations with Wasserstein Distance
    Wei Fan, Kunpeng Liu, Rui Xie, Hao Liu, Hui Xiong, Yanjie Fu · 2021 · Proceedings
58. Investigating Trade-offs in Utility, Fairness and Differential Privacy in Neural Networks
    Marlotte Pannekoek, Giacomo Spigler · 2021 · arXiv (Cornell University)
59. Achieving Model Fairness in Vertical Federated Learning
    Changxin Liu, Zhenan Fan, Zirui Zhou, Yang Shi, Jian Pei, Lingyang Chu, Yong Zhang · 2021 · arXiv (Cornell University)
60. Embedding AI ethics in the data lifecycle: A framework for enterprise AI governance
    Xinping Huang, Tianqi Kou, Qianwen Zhou · 2026 · Technology in Society
61. Promoting fairness in activity recognition algorithms for patient’s monitoring and evaluation systems in healthcare
    Ciro Mennella, Massimo Esposito, Giuseppe De Pietro, Umberto Maniscalco · 2024 · Computers in Biology and Medicine
62. Patient centric trustworthy AI in medical analysis and disease prediction: A Comprehensive survey and taxonomy
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63. A comprehensive analysis of gender, racial, and prompt-induced biases in large language models
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64. Design of quantum computing-based avain navigation optimization algorithm for parameter estimation of input nonlinear output error model with key term separation
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65. Navigating fairness: practitioners’ understanding, challenges, and strategies in AI/ML development
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66. A Taxonomy of Generative Artificial Intelligence in Health Economics and Outcomes Research: An ISPOR Working Group Report
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67. Beyond RMSE and MAE: Introducing EAUC to Unmask Hidden Bias and Unfairness in Dyadic Regression Models
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68. Robust Personalized Federated Learning under Demographic Fairness Heterogeneity
    Alycia N. Carey, Wei Du, Xintao Wu · 2022 · IEEE International Conference on Big Data (BigData)
69. Fair CRISP-DM: Embedding Fairness in Machine Learning (ML) Development Life Cycle
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70. Counterfactual Fairness Is Basically Demographic Parity
    Lucas Rosenblatt, R. Teal Witter · 2023 · Proceedings of the AAAI Conference on Artificial Intelligence
71. Fairness in Algorithmic Profiling: A German Case Study
    Christoph A. Kern, Ruben L. Bach, Hannah Mautner, Frauke Kreuter · 2021 · MADOC (University of Mannheim)
72. Modeling Techniques for Machine Learning Fairness: A Survey
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73. Predicting retracted research: a dataset and machine learning approaches
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74. Fairness Concerns in App Reviews: A Study on AI-Based Mobile Apps
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75. Responsible Artificial Intelligence for Mental Health Disorders: Current Applications and Future Challenges
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76. EduStudio: towards a unified library for student cognitive modeling
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77. Equitable hospital length of stay prediction for patients with learning disabilities and multiple long-term conditions using machine learning
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78. How fair are we? From conceptualization to automated assessment of fairness definitions
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79. Data augmentation via diffusion model to enhance AI fairness
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80. Unveiling Group-Specific Distributed Concept Drift: A Fairness Imperative in Federated Learning
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81. A Survey on Bias in Machine Learning Research
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82. FairIF: Boosting Fairness in Deep Learning via Influence Functions with Validation Set Sensitive Attributes
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83. Connecting Fairness in Machine Learning with Public Health Equity
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84. Fairness Hacking: The Malicious Practice of Shrouding Unfairness in Algorithms
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85. What Do the Regulators Mean? A Taxonomy of Regulatory Principles for the Use of AI in Financial Services
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86. A Survey of Bias and Fairness in Healthcare AI
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87. Fairframe: a fairness framework for bias detection and mitigation in news
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88. Vieses no Aprendizado de Máquina e suas Implicações Sociais: Um Estudo de Caso no Reconhecimento Facial
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89. Using Pareto simulated annealing to address algorithmic bias in machine learning
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90. Data preprocessing to improve fairness in machine learning models: An application to the reintegration process of demobilized members of armed groups in Colombia
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91. Toward a Responsible Fairness Analysis: From Binary to Multiclass and Multigroup Assessment in Graph Neural Network-Based User Modeling Tasks
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92. Artificial Intelligence and Aging in Place: A Scoping Review of Current Applications and Future Directions
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93. A Guide to Machine Learning Epistemic Ignorance, Hidden Paradoxes, and Other Tensions
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94. Personalized federated learning with fairness, robustness, and collaboration incentives
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95. Classification Utility, Fairness, and Compactness via Tunable Information Bottleneck and Rényi Measures
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96. Türkiye’de Halk Kütüphanesi Çalışanlarının Yapay Zekâya Yönelik Genel Tutumları
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97. Catching Silent Failures: A Machine Learning Model Monitoring and Explainability Survey
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98. On Measurement Validity and Language Models: Increasing Validity and Decreasing Bias with Instructions
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99. Fair XIDS: Ensuring fairness and transparency in intrusion detection models
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100. Fair streaming feature selection
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